AI and Generative AI-Driven Automation for Multi-Cloud and Hybrid Cloud Architectures: Enhancing Security, Performance, and Operational Efficiency

The emergence of cloud and hybrid cloud structures presents eCommerce firms with the adaptability and robustness needed to manage expansion and varying user requirements effectively. However, this also brings about challenges concerning security enhancements, distribution of workloads, and cost-effectiveness optimization. Traditional cloud management models often need help to meet these evolving demands efficiently. This research presents a system that leverages Artificial Intelligence (AI) and Generative AI (Gen AI) to effectively automate and enhance cloud and hybrid infrastructures for ecommerce websites. The system adapts infrastructure to traffic times like holidays or sales events by utilizing AI to scale resources as needed. It conserves resources during low user activity periods such as overnight. Ensuring optimal system performance and availability during peak traffic times while cutting costs during traffic periods is essential for cost-effectiveness and efficient resource management. In addition, AI-powered security automation safeguards against changing cyber dangers, and compliance automation guarantees conformity with rules like PCI DSS for payment handling. This report also delves into merging Gen AI into cloud coordination systems, facilitating workflows, and enhancing eCommerce processes. The outcome is a significant drop in operational expenses, a quicker service rollout, and decreased security breaches. Through real-world eCommerce case studies, this paper provides actionable insights for cloud engineers and architects on leveraging AI-driven cloud management to enhance performance, security, and cost-efficiency in multi-cloud and hybrid environments, ensuring seamless user experiences and business continuity.